Ph.D Students


In Progress


  1. Ashish Srivastava (ERP; joint guidance with Prof. M.Narasimha Murty: Joined August 2019

  2. Joji Joseph (RBCCPS; joint guidance with Prof. Bharadwaj Amrutur): Joined August 2019

  3. Lakshmi Mandal: Joined August 2020

  4. Kaustubh Kartikey: Joined August 2022

  5. Prashansa Panda: Joined August 2022

  6. Naman: Joined August 2022

  7. Onkar Deokar: August 2024



Former Students


  1. Soumyajit Guin: Algorithms for various cost criteria in Reinforcement Learning, 2025.

  2. Vivek V.P: Single and Multi-Agent Finite Horizon Reinforcement Learning Algorithms for Smart Grids, thesis defended, July 2024

  3. D. Raghuram Bharadwaj: Reinforcement Learning Algorithms for Off-Policy, Multi-Agent Learning and their Applications to Smart Grids, graduated, 2022

  4. Sindhu P.R.: Algorithms for Challenges to Practical Reinforcement Learning, graduated, 2021

  5. Chandramouli K., Algorithms for Stochastic Optimization, Statistical Estimation and Markov Decision Processes, graduated 2020

  6. Indu John: Decision Making under Uncertainty: Reinforcement Learning Algorithms and Aaplications in Cloud Computing, Crowdsourcing and Predictive Analytics, graduated 2020

  7. Vinayaka G. Yaji: Stochastic Approximation with Set-Valued Maps and Markov Noise: Theoretical Foundations and Applications, graduated 2018

  8. Prasenjit Karmakar: Stochastic Approximation with Markov Noise: Analysis and Applications in Reinforcement Learning, graduated 2018

  9. Arunselvan Ramaswamy: Stochastic Approximation Algorithms with Set-Valued Dynamics: Theory and Applications, graduated 2017

  10. Ajin George Joseph: Optimization Algorithms for Deterministic, Stochastic and Reinforcement Learning Settings, graduated 2017

  11. Ranganath B.N.: Scalable Sparse Bayesian Nonparametric and Matrix Tri-factorization Models for Text Mining Applications, graduated 2017

  12. K.J. Prabu Chandran: Feature Adaptation Algorithms for Reinforcement Learning with Applications to Wireless Sensor Networks and Road Traffic Control, graduated 2016

  13. Chandrashekar Lakshmi Narayanan: Approximate Dynamic Programming and Reinforcement Learning - Algorithms, Analysis and An Application, graduated 2016

  14. Lakshmanan K : Online Learning and Simulation based Algorithms for Stochastic Optimization, graduated 2013.

  15. Prashanth L.A : Resource Allocation under Uncertainty: Studies in Vehicular Traffic Control, Service Systems, Sensor Networks and Mechanism Design, graduated 2013.

  16. H.L. Prasad : Algorithms for Stochastic Games and Service Systems, graduated 2013.

  17. Vivek Kumar Mishra : Simulation Based Methods for Optimization, graduated 2012.

  18. Mohammed Shahid Abdulla : Simulation Based Algorithms for Markov Decision Processes and Stochastic Optimization, graduated 2008.

  19. Ambedkar Dukkipati (joint guidance with Prof. M. Narasimha Murty) : On Generalized Measures of Information with Maximum and Minimum Entropy Prescriptions, graduated 2007.

  20. Viswanath Pulabaigari (joint guidance with Prof. M. Narasimha Murty) : Pattern Synthesis Techniques and Compact Data Representation Schemes for Efficient Nearest Neighbor Classification, graduated 2005.